Patrick Glass1, Eric Dietz2, Pamela Aaltenon3. 1. Formerly a Graduate Student at Purdue University Homeland Security Institute, Cameron, North Carolina; Major in the US Army, Fort Bragg, North Carolina. 2. Professor of Computer and Information Technology and Director of the Purdue University Homeland Security Institute, West Lafayette, Indiana. 3. Professor Emerita, Purdue University, West Lafayette, Indiana.
Abstract
OBJECTIVE: The objective of this research was to develop a computer simulation model that will provide the most optimal allocation of resources for a point of distribution (POD) site. DESIGN: A baseline assessment was conducted by participants establishing POD sections with no guidance from the investigator. A computer model was built with four stations: triage, registration, screening, and dispensing. The information from the computer simulation was used to design the allocation of volunteers for the experimental group. Once the data were collected, a two-sample t test was used to determine the significance of the difference between the average times of the two groups to complete the POD. SETTING: The POD site was conducted indoors with volunteers acting as patients, and volunteer nursing students, and pharmacy students acting as POD workers. Volunteers were divided into two groups, group B, experimental and group A, control. Time was recorded using a digital time-stamp at the beginning and at the end of the POD. INTERVENTIONS: The researcher inputted the total number of volunteers into the model, and the model generated the most applicable ratio for distribution of human capital: a one-to-one ratio of screeners to dispensers. MAIN OUTCOME MEASURES: The mean time for Group A was 4.55 minutes (95% CI: 4.27, 4.83). The mean time for group B was 3.05 minutes (95% CI: 2.79, 3.31). A two-sample t test and Analysis of Variance of these data show that the difference is meaningful (p < 0.001). RESULTS: The results show that a discrete-event computer simulation can be used to identify the most efficient use of resources in order to decrease the amount of time that patients are required to participate. CONCLUSIONS: The discrete-event computer simulation model was found to be effective at identifying ways to in-crease efficiency and reduce the overall time required by patients to complete the POD.
RCT Entities:
OBJECTIVE: The objective of this research was to develop a computer simulation model that will provide the most optimal allocation of resources for a point of distribution (POD) site. DESIGN: A baseline assessment was conducted by participants establishing POD sections with no guidance from the investigator. A computer model was built with four stations: triage, registration, screening, and dispensing. The information from the computer simulation was used to design the allocation of volunteers for the experimental group. Once the data were collected, a two-sample t test was used to determine the significance of the difference between the average times of the two groups to complete the POD. SETTING: The POD site was conducted indoors with volunteers acting as patients, and volunteer nursing students, and pharmacy students acting as POD workers. Volunteers were divided into two groups, group B, experimental and group A, control. Time was recorded using a digital time-stamp at the beginning and at the end of the POD. INTERVENTIONS: The researcher inputted the total number of volunteers into the model, and the model generated the most applicable ratio for distribution of human capital: a one-to-one ratio of screeners to dispensers. MAIN OUTCOME MEASURES: The mean time for Group A was 4.55 minutes (95% CI: 4.27, 4.83). The mean time for group B was 3.05 minutes (95% CI: 2.79, 3.31). A two-sample t test and Analysis of Variance of these data show that the difference is meaningful (p < 0.001). RESULTS: The results show that a discrete-event computer simulation can be used to identify the most efficient use of resources in order to decrease the amount of time that patients are required to participate. CONCLUSIONS: The discrete-event computer simulation model was found to be effective at identifying ways to in-crease efficiency and reduce the overall time required by patients to complete the POD.